ANALYSIS OF STRUCTURES OF COVARIANCE AND REPEATABILITY IN GUAVA SEGREGANTING POPULATION

Detalhes bibliográficos
Autor(a) principal: Quintal, Silvana Silva Red
Data de Publicação: 2017
Outros Autores: Viana, Alexandre Pio, Campos, Bianca Machado, Vivas, Marcelo, Amaral Júnior, Antonio Teixeira do
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Caatinga
Texto Completo: https://periodicos.ufersa.edu.br/caatinga/article/view/6211
Resumo: The present study was conducted with the objective of analyzing the covariance structure and repeatability estimates of the variables related to guava productivity, such as fruit weight (FW), fruit number (FN) and fruit production (FP) of three harvests, in 95 genotypes of a segregating population. The study also aims to choose the most appropriate covariance structure of the observations within the same individual by means of AIC (Akaike's Information Criterion) and SBC (Schwarz's Bayesian Criterion) criteria. A covariance structure between repeated measures could be incorporated into the statistical model, with the self-regression and compound symmetry forms being the most adequate. The values of repeatability coefficients obtained for FW (0.25), FN (0.14), and FP (0.29) were considered low, indicating that the three harvests were not sufficient to select the best individuals with greater accuracy for the study population. For the variables PF and FP, estimates of accuracy around 0.50 could be obtained from five measurements, while for the variable FN more harvests would be necessary. These values indicate that in guava-segregating populations, evaluations in the first harvests are not enough to select more stable genotypes for the variables considered in this study.
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spelling ANALYSIS OF STRUCTURES OF COVARIANCE AND REPEATABILITY IN GUAVA SEGREGANTING POPULATIONANÁLISE DE ESTRUTURAS DE COVARIÂNCIAS E REPETIBILIDADE EM POPULAÇÃO SEGREGANTE DE GOIABEIRACovariance structure. Coefficient of repeatability. Psidium guajava.Estrutura de covariância. Coeficiente de repetibilidade. Psidium guajava.The present study was conducted with the objective of analyzing the covariance structure and repeatability estimates of the variables related to guava productivity, such as fruit weight (FW), fruit number (FN) and fruit production (FP) of three harvests, in 95 genotypes of a segregating population. The study also aims to choose the most appropriate covariance structure of the observations within the same individual by means of AIC (Akaike's Information Criterion) and SBC (Schwarz's Bayesian Criterion) criteria. A covariance structure between repeated measures could be incorporated into the statistical model, with the self-regression and compound symmetry forms being the most adequate. The values of repeatability coefficients obtained for FW (0.25), FN (0.14), and FP (0.29) were considered low, indicating that the three harvests were not sufficient to select the best individuals with greater accuracy for the study population. For the variables PF and FP, estimates of accuracy around 0.50 could be obtained from five measurements, while for the variable FN more harvests would be necessary. These values indicate that in guava-segregating populations, evaluations in the first harvests are not enough to select more stable genotypes for the variables considered in this study.O presente estudo foi conduzido com o objetivo de analisar estrutura de covariância e estimativas de repetibilidade das variáveis relacionadas à produtividade da goiabeira como massa dos frutos (MF), número de frutos (NF) e produção de frutos (PROD) de três safras, em 95 genótipos de uma população segregante. E por meio dos critérios de AIC (Akaike’s Information Criterion) e SBC (Schwarz’s Bayesian Criterion) escolher a estrutura de covariância mais adequada das observações dentro de um mesmo indivíduo. Foi possível incorporar ao modelo estatístico, uma estrutura de covariância entre medidas repetidas, sendo as formas autorregressiva e simetria composta as mais adequadas. Os valores dos coeficientes de repetibilidade obtidos para PF (0,25), NF (0,14) e PROD (0,29) foram considerados baixos, indicando que para a população em estudo as três safras realizadas não foram suficientes para selecionar os melhores indivíduos com maior acurácia. Para as variáveis PF e PROD, a partir de cinco medições seria possível a obtenção de estimativas de acurácias em torno de 0,50. Enquanto que para a variável NF, observou-se que mais safras seriam necessárias. Estes valores indicam que em populações segregantes de goiabeira, avaliações nas primeiras safras, não são suficientes para seleção de genótipos mais estáveis para as variáveis consideradas neste estudo.Universidade Federal Rural do Semi-Árido2017-06-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufersa.edu.br/caatinga/article/view/621110.1590/1983-21252017v30n408rcREVISTA CAATINGA; Vol. 30 No. 4 (2017); 885-891Revista Caatinga; v. 30 n. 4 (2017); 885-8911983-21250100-316Xreponame:Revista Caatingainstname:Universidade Federal Rural do Semi-Árido (UFERSA)instacron:UFERSAenghttps://periodicos.ufersa.edu.br/caatinga/article/view/6211/pdfQuintal, Silvana Silva RedViana, Alexandre PioCampos, Bianca MachadoVivas, MarceloAmaral Júnior, Antonio Teixeira doinfo:eu-repo/semantics/openAccess2023-07-20T11:30:00Zoai:ojs.periodicos.ufersa.edu.br:article/6211Revistahttps://periodicos.ufersa.edu.br/index.php/caatinga/indexPUBhttps://periodicos.ufersa.edu.br/index.php/caatinga/oaipatricio@ufersa.edu.br|| caatinga@ufersa.edu.br1983-21250100-316Xopendoar:2023-07-20T11:30Revista Caatinga - Universidade Federal Rural do Semi-Árido (UFERSA)false
dc.title.none.fl_str_mv ANALYSIS OF STRUCTURES OF COVARIANCE AND REPEATABILITY IN GUAVA SEGREGANTING POPULATION
ANÁLISE DE ESTRUTURAS DE COVARIÂNCIAS E REPETIBILIDADE EM POPULAÇÃO SEGREGANTE DE GOIABEIRA
title ANALYSIS OF STRUCTURES OF COVARIANCE AND REPEATABILITY IN GUAVA SEGREGANTING POPULATION
spellingShingle ANALYSIS OF STRUCTURES OF COVARIANCE AND REPEATABILITY IN GUAVA SEGREGANTING POPULATION
Quintal, Silvana Silva Red
Covariance structure. Coefficient of repeatability. Psidium guajava.
Estrutura de covariância. Coeficiente de repetibilidade. Psidium guajava.
title_short ANALYSIS OF STRUCTURES OF COVARIANCE AND REPEATABILITY IN GUAVA SEGREGANTING POPULATION
title_full ANALYSIS OF STRUCTURES OF COVARIANCE AND REPEATABILITY IN GUAVA SEGREGANTING POPULATION
title_fullStr ANALYSIS OF STRUCTURES OF COVARIANCE AND REPEATABILITY IN GUAVA SEGREGANTING POPULATION
title_full_unstemmed ANALYSIS OF STRUCTURES OF COVARIANCE AND REPEATABILITY IN GUAVA SEGREGANTING POPULATION
title_sort ANALYSIS OF STRUCTURES OF COVARIANCE AND REPEATABILITY IN GUAVA SEGREGANTING POPULATION
author Quintal, Silvana Silva Red
author_facet Quintal, Silvana Silva Red
Viana, Alexandre Pio
Campos, Bianca Machado
Vivas, Marcelo
Amaral Júnior, Antonio Teixeira do
author_role author
author2 Viana, Alexandre Pio
Campos, Bianca Machado
Vivas, Marcelo
Amaral Júnior, Antonio Teixeira do
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Quintal, Silvana Silva Red
Viana, Alexandre Pio
Campos, Bianca Machado
Vivas, Marcelo
Amaral Júnior, Antonio Teixeira do
dc.subject.por.fl_str_mv Covariance structure. Coefficient of repeatability. Psidium guajava.
Estrutura de covariância. Coeficiente de repetibilidade. Psidium guajava.
topic Covariance structure. Coefficient of repeatability. Psidium guajava.
Estrutura de covariância. Coeficiente de repetibilidade. Psidium guajava.
description The present study was conducted with the objective of analyzing the covariance structure and repeatability estimates of the variables related to guava productivity, such as fruit weight (FW), fruit number (FN) and fruit production (FP) of three harvests, in 95 genotypes of a segregating population. The study also aims to choose the most appropriate covariance structure of the observations within the same individual by means of AIC (Akaike's Information Criterion) and SBC (Schwarz's Bayesian Criterion) criteria. A covariance structure between repeated measures could be incorporated into the statistical model, with the self-regression and compound symmetry forms being the most adequate. The values of repeatability coefficients obtained for FW (0.25), FN (0.14), and FP (0.29) were considered low, indicating that the three harvests were not sufficient to select the best individuals with greater accuracy for the study population. For the variables PF and FP, estimates of accuracy around 0.50 could be obtained from five measurements, while for the variable FN more harvests would be necessary. These values indicate that in guava-segregating populations, evaluations in the first harvests are not enough to select more stable genotypes for the variables considered in this study.
publishDate 2017
dc.date.none.fl_str_mv 2017-06-14
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufersa.edu.br/caatinga/article/view/6211
10.1590/1983-21252017v30n408rc
url https://periodicos.ufersa.edu.br/caatinga/article/view/6211
identifier_str_mv 10.1590/1983-21252017v30n408rc
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.ufersa.edu.br/caatinga/article/view/6211/pdf
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal Rural do Semi-Árido
publisher.none.fl_str_mv Universidade Federal Rural do Semi-Árido
dc.source.none.fl_str_mv REVISTA CAATINGA; Vol. 30 No. 4 (2017); 885-891
Revista Caatinga; v. 30 n. 4 (2017); 885-891
1983-2125
0100-316X
reponame:Revista Caatinga
instname:Universidade Federal Rural do Semi-Árido (UFERSA)
instacron:UFERSA
instname_str Universidade Federal Rural do Semi-Árido (UFERSA)
instacron_str UFERSA
institution UFERSA
reponame_str Revista Caatinga
collection Revista Caatinga
repository.name.fl_str_mv Revista Caatinga - Universidade Federal Rural do Semi-Árido (UFERSA)
repository.mail.fl_str_mv patricio@ufersa.edu.br|| caatinga@ufersa.edu.br
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